Technical Field
The present invention relates generally to data analysis and more particularly, but not by way of limitation, to systems and methods for identifying related credit inquiries.
History of Related Art
Identity theft is one of the fastest-growing crimes in the United States and worldwide. Identity theft generally involves a use of personally-identifying information (PII) that is not authorized by an owner of the PII. PII, as used herein, refers to information that can be used to uniquely identify, contact, or locate a person or can be used with other sources to uniquely identify, contact, or locate a person. PII may include, but is not limited to, social security numbers (SSN), bank or credit card account numbers, passwords, birth dates, and addresses. Identity theft may include, for example, an unauthorized change to PII or an unauthorized use of PII to access resources or to obtain credit or other benefits.
Since identity theft affects both businesses and consumers, there is a need to effectively alert consumers of potential identity theft. Part of an effective alert system can be notifying consumers of new credit inquiries using their PII. In that regard, various credit-monitoring services generate and present alerts to monitored consumers as new credit inquiries appear on their credit report. However, in jurisdictions such as the United States, distinct credit reports are maintained by multiple credit bureaus. Therefore, when the monitored consumer begins shopping for a car loan, home mortgage, credit card, or the like, multiple credit inquiries may be initiated by multiple creditors relative to multiple credit reports. This can result in voluminous credit alerts being generated and presented to the monitored consumer even though the alerts may relate to a single prospective transaction. The volume of redundant information can reduce the effectiveness of credit monitoring, for example, by training consumers to ignore alerts or by discouraging them from monitoring their credit at all.